Compare models

Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

Perceptron Mk1.5Perceptron Remove
Transcribe 1 ProFish Audio Remove
MiniMax M2MiniMax Remove
Gemini 3.5 TranscribeGoogle Remove

4 is the maximum. Remove one to add another.

perceptron-mk1.5 vs transcribe-1-pro vs minimax-m2 vs gemini-3.5-transcribe
Attribute	Perceptron Mk1.5perceptron-mk1.5	Transcribe 1 Protranscribe-1-pro	MiniMax M2minimax-m2	Gemini 3.5 Transcribegemini-3.5-transcribe
Pricing
Input	$0.15 / 1M	— Not priced per input token	$0.15 / 1M	— Not priced per input token
Output	$1.50 / 1M	— Not priced per output token	$0.45 / 1M	— Not priced per output token
Cache Write (5m)	$0.15 / 1M	Not applicable	$0.15 / 1M	Not applicable
Cache Write (1h)	$0.15 / 1M	Not applicable	$0.15 / 1M	Not applicable
Cache Read	$0.15 / 1M	Not applicable	$0.15 / 1M	Not applicable
Web Search	$0 / 1M	$0 / 1M	$0 / 1M	$0 / 1M
Context
Max context	36.9K	N/A	196.6K	98.3K
Max output	N/A	N/A	N/A	N/A
Capabilities
Vision	No	No	Yes	Yes
Function Calling	No	No	Yes	Yes
JSON Mode	No	No	Yes	No
Streaming	Yes	No	Yes	No
Catalogue
Provider	Perceptron	Fish Audio	MiniMax	Google
Category	chat	voice	chat	voice
Charge type	Pay As You Go	Pay As You Go	Pay As You Go	Pay As You Go
Released	2026-09-25	2026-09-24	—	2026-09-25
Description
Summary	Perceptron Mk1.5 chat model that accepts audio input. Audio and text input are billed per token.	Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <\|speaker:0\|>. Billed per second of audio.	MiniMax-M2 is a compact, high-efficiency model with 10B active (230B total) parameters, optimized for coding and agentic workflows. It delivers near-frontier reasoning and tool use, excels at multi-file coding tasks and compile-run-fix loops, and performs strongly on benchmarks like SWE-Bench and Terminal-Bench. It also handles long-horizon planning and recovery in agent evaluations, ranking among the top open models across reasoning domains. With fast inference and low cost, it’s ideal for large-scale agents and developer assistants — and works best when reasoning is preserved across turns.	Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.